
High-performance Parallel Computing
Research Title: Development of cost-efficient parallel computing algorithms of governing equations related to turbulence.
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Supervisor: Dr. Omer San, Oklahoma State University.
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Goal: This is a side project that I pursue out of personal interest whenever I take a break from my primary research. The primary goal of this work is to improve the parallel computing performance of complex multiscale simulations by reducing computational cost and enhancing computational acceleration.
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Tools Used: Fortran, ParaView, Tecplot, Python​
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Summary: Our codes use MPI-based domain decomposition, data exchange APIs, and the OpenMPI standard library for parallel implementation, with visualization performed in ParaView and Tecplot. As this was an independent, interest-driven project rather than a funded effort, our work primarily focused on academic benchmark cases, including 3D channel flow, Kelvin–Helmholtz, Rayleigh–Taylor, and Richtmyer–Meshkov instabilities in 2D and 3D, and the 3D Taylor–Green vortex. A summary of this parallel computing research was presented as a poster at the CADRE Conference in Stillwater, Oklahoma, USA.
